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als-statistics

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Modular JS statistics toolkit for Node.js and the browser: descriptive stats, correlations (Pearson/Spearman/Kendall), t-tests & ANOVA (Student/Welch), reliability (Cronbach’s alpha), regression (linear/logistic), clustering (DBSCAN/HDBSCAN), and table/co

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<title>Data Managing — Tables & Columns</title> <description>How ALS Statistics structures and validates your data. Learn Columns (validation, caching, safe mutations) and Tables (alignment, transforms, analysis shortcuts), with clear examples.</description> <keywords>table, column, data validation, caching, alignment, sort, filter, recode, compute, htmlTable, correlate, compare means</keywords> # Data managing (Tables and Columns) This section explains how data flows through **Columns**, **Tables** and **Statistics**: validation rules, caching, safe updates, and the most common operations you’ll use before running analytics. --- ## Notes & pitfalls - **Always mutate via API.** Use `Column` mutators or the `values` setter; avoid direct array mutation to keep caches correct. - **Invalids.** `Column.invalid` stores indices of rejected values; descriptives and analyses ignore them. - **Mutability.** Most `Table` methods are in-place and return `this`. Prefer `clone()` when you need a safe branch. - **Alignment.** If you disable alignment and keep ragged columns, be mindful when exporting rows or running analyses that expect equal lengths. - **HTML output.** `htmlTable()` is for quick previews; for full reports, prefer exporting rows and rendering via your own templates.